1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
|
/*
* Copyright (c) 2017, 2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef ARM_COMPUTE_GC
#error "This example needs to be built with -DARM_COMPUTE_GC"
#endif /* ARM_COMPUTE_GC */
#include "arm_compute/runtime/GLES_COMPUTE/GCFunctions.h"
#include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h"
#include "half/half.hpp"
#include "utils/Utils.h"
using namespace arm_compute;
using namespace utils;
class GCDCExample : public Example
{
public:
void do_setup(int argc, char **argv) override
{
ARM_COMPUTE_UNUSED(argc);
ARM_COMPUTE_UNUSED(argv);
// init instance
GCScheduler::get().default_init();
const TensorShape src_shape = TensorShape{ 11U /* W */, 13U /* H */, 4U /* C */, 3U /* N */ };
const unsigned int kernel_size = 3;
const int stride_x = 1;
const int stride_y = 1;
const int pad_x = 0;
const int pad_y = 0;
const unsigned int num_kernels = 256;
const DataType data_type = DataType::F16;
// generate shape
const TensorShape weights_shape(kernel_size, kernel_size, src_shape.z(), num_kernels);
const TensorShape bias_shape(num_kernels);
const PadStrideInfo pad_info(stride_x, stride_y, pad_x, pad_y, DimensionRoundingType::FLOOR);
// output shape should be 9*11*256*3 (W*H*C*N)
const TensorShape dst_shape = get_output_shape(src_shape, weights_shape, pad_info);
// create tensors
src.allocator()->init(TensorInfo(src_shape, 1, data_type));
weights.allocator()->init(TensorInfo(weights_shape, 1, data_type));
bias.allocator()->init(TensorInfo(bias_shape, 1, data_type));
dst.allocator()->init(TensorInfo(dst_shape, 1, data_type));
// configure layer
conv.configure(&src, &weights, &bias, &dst, pad_info);
// allocate tensors
src.allocator()->allocate();
weights.allocator()->allocate();
bias.allocator()->allocate();
dst.allocator()->allocate();
// To demonstrate how to fill tensor with some values...
src.map();
Window window;
window.use_tensor_dimensions(src_shape);
Iterator it(&src, window);
execute_window_loop(window, [&](const Coordinates & id)
{
*reinterpret_cast<half_float::half *>(it.ptr()) = half_float::half(1.f);
});
src.unmap();
}
void do_run() override
{
// run the layer
conv.run();
}
void do_teardown() override
{
// check result
dst.map();
// do something
dst.unmap();
}
private:
GCTensor src{}, weights{}, bias{}, dst{};
GCDirectConvolutionLayer conv{};
TensorShape get_output_shape(TensorShape in_shape, TensorShape kernel_shape, const PadStrideInfo &info)
{
TensorShape out_shape(in_shape);
const std::pair<unsigned int, unsigned int> scaled_dims = scaled_dimensions(in_shape.x(),
in_shape.y(),
kernel_shape.x(),
kernel_shape.y(),
info);
out_shape.set(0, scaled_dims.first);
out_shape.set(1, scaled_dims.second);
out_shape.set(2, kernel_shape[3]);
return out_shape;
}
};
/** Main program for directconvolution test
*
* @param[in] argc Number of arguments
* @param[in] argv Arguments
*/
int main(int argc, char **argv)
{
return utils::run_example<GCDCExample>(argc, argv);
}
|